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Data · dataset · 2025

Prediction of radionuclide diffusion enabled by missing data imputation and ensemble machine learning

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Missing values in radionuclide diffusion datasets can undermine the predictive accuracy and robustness of machine learning models.

Description

A regression-based missing data imputation method using light gradient boosting machine algorithm was employed to impute over 60% of the missing data.

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Catalogue records · 1

Topics

Inferred from text
Machine learning 72%
Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.j00186.007109 d agoJSON v1
FieldAssertionExtractorEvidence
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